Avoid Overfitting Using Regularization in TensorFlow
In this 2-hour long project-based course, you will learn the basics of using weight regularization and dropout regularization to reduce over-fitting in an image classification problem. By the end of this project, you will have created, trained, and evaluated a Neural Network model that, after the training and regularization, will predict image classes of input examples with similar accuracy for both training and validation sets. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
由 RD 提供2021年1月30日
Good introduction to regularization techniques. It's nice to learn these techniques with a relevant, but simple, example code.
由 IR 提供2020年8月6日
please enable me to reset the deadlines as i was unable to complete..